Irene Nieto is a Computer Vision Engineer with 13 years of software experience and 7+ years focused on robotics and space R&D, currently building vision and data-fusion algorithms at Magic Leap. She designs object detection/tracking, VSLAM/VO localisation, and 3D/DEM mapping pipelines that fuse visual, ranging and inertial sensors for both planetary and in-orbit applications. Proficient in C++, Python, ROS, OpenCV and PCL, she pairs research-grade algorithm development with production engineering—evidenced by contributions to the LibreScanner/horus 3D scanning engine where she fixed core phase-shift bugs and improved capture pipelines. Previously she led teams and departments, managing over 20 engineers while moving projects from prototyping to product at companies like BQ and Space Applications Services. Bilingual in Spanish and English (with intermediate French), she combines fast learning and clear communication with hands-on firmware, backend and GUI experience across consumer and space domains. Her blend of technical leadership and low-level debugging skill makes her effective at turning experimental perception systems into robust fieldable solutions.
13 years of coding experience
7 years of employment as a software developer
Charles III University of Madrid (Universidad Carlos III de Madrid)
Contributions:87 commits, 29 pushes, 17 branches in 3 months
Contributions summary:Irene's primary contribution focused on fixing phase shift issues and performing refactoring within the `scan.py` file. This involved modifications to the `_processThread` and `_captureThread` methods, as well as redefining the `_processThread` in the parent class `Scan`. The user also addressed a bug related to zeroes matrix and incorporated timeout mechanisms when setting various parameters, streamlining the workflow. These changes indicate a focus on improving the core scanning engine's functionality and resolving operational issues.
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Irene Nieto - Computer Vision Engineer at Magic Leap